2019 IEEE National Aerospace and Electronics Conference (NAECON)最新文献

High-index micro-cones for focusing and concentrating light in MWIR focal plane arrays 用于MWIR焦平面阵列聚焦和聚光的高折射率微锥

2019 IEEE National Aerospace and Electronics Conference (NAECON) Pub Date : 2019-07-01 DOI: 10.1109/NAECON46414.2019.9057919

B. Jin, Grant W. Bidney, A. Brettin, N. Limberopoulos, I. Anisimov, A. Urbas, Hanyang Li, V. Astratov

引用次数: 3

Smart Phone as Toolbox for Height Measurement 智能手机作为高度测量工具箱

2019 IEEE National Aerospace and Electronics Conference (NAECON) Pub Date : 2019-07-01 DOI: 10.1109/NAECON46414.2019.9058290

A. Razaque, Fathi H. Amsaad, Cai Mengjie Cherry, Lin Jiahui Linda, A. Oun

引用次数: 0

Improving Cellphone Microscopy Imaging with Contact Ball Lenses 用接触球镜片改进手机显微镜成像

2019 IEEE National Aerospace and Electronics Conference (NAECON) Pub Date : 2019-07-01 DOI: 10.1109/NAECON46414.2019.9058104

Grant W. Bidney, A. Brettin, B. Jin, N. Limberopoulos, I. Anisimov, Hanyang Li, A. Maslov, V. Astratov

引用次数: 1

High Performance SqueezeNext for CIFAR-10 高性能SqueezeNext for CIFAR-10

2019 IEEE National Aerospace and Electronics Conference (NAECON) Pub Date : 2019-07-01 DOI: 10.1109/NAECON46414.2019.9058217

Jayan Kant Duggal, M. El-Sharkawy

{"title":"High Performance SqueezeNext for CIFAR-10","authors":"Jayan Kant Duggal, M. El-Sharkawy","doi":"10.1109/NAECON46414.2019.9058217","DOIUrl":"https://doi.org/10.1109/NAECON46414.2019.9058217","url":null,"abstract":"CNNs is the foundation for deep learning and computer vision domain enabling applications such as autonomous driving, face recognition, automatic radiology image reading, etc. But, CNN is a algorithm which is memory and computationally intensive. DSE of neural networks and compression techniques have made convolution neural networks memory and computationally efficient. It improved the CNN architectures and made it more suitable to implement on real-time embedded systems. This paper proposes an efficient and a compact CNN to ameliorate the performance of existing CNN architectures. The intuition behind this proposed architecture is to supplant convolution layers with a more sophisticated block module and to develop a compact architecture with a competitive accuracy. Further, explores the bottleneck module and squeezenext basic block structure. The state-of-the-art squeezenext baseline architecture is used as a foundation to recreate and propose a high performance squeezenext architecture. The proposed architecture is further trained on the CIFAR-10 dataset from scratch. All the training and testing results are visualized with live loss and accuracy graphs. Focus of this paper is to make an adaptable and a flexible model for efficient CNN performance which can perform better with the minimum tradeoff between model accuracy, size, and speed. Finally, the conclusion is made that the performance of CNN can be improved by developing an architecture for a specific dataset. The purpose of this paper is to introduce and propose high performance squeezenext for CIFAR-10.","PeriodicalId":193529,"journal":{"name":"2019 IEEE National Aerospace and Electronics Conference (NAECON)","volume":"77 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116093068","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

A generalized equivalent circuit model for large-scale battery packs with cell-to-cell variation 具有电池间变化的大型电池组的广义等效电路模型

2019 IEEE National Aerospace and Electronics Conference (NAECON) Pub Date : 2019-07-01 DOI: 10.1109/NAECON46414.2019.9057803

Yaping Cai, Massimo Cancian, M. D’Arpino, G. Rizzoni

{"title":"A generalized equivalent circuit model for large-scale battery packs with cell-to-cell variation","authors":"Yaping Cai, Massimo Cancian, M. D’Arpino, G. Rizzoni","doi":"10.1109/NAECON46414.2019.9057803","DOIUrl":"https://doi.org/10.1109/NAECON46414.2019.9057803","url":null,"abstract":"A critical issue in large-scale battery pack is the capability of assessing the impact of cell-to-cell variation on the pack/module performance. The inhomogeneity of cell parameters is mainly due to manufacturing tolerances, cell degradation, and temperature gradients, and leads to unbalanced current and voltage distribution in the pack. In this paper, a generalized equivalent circuit model is proposed that effectively allows estimating the current and voltage differences between cells/strings in a pack as function of the system architecture and parameters. The model is based on a simplified equivalent circuit model that separates the healthy cells from the ones affected by parameters variation. The proposed methodology has been applied to several pack configurations, typically used for automotive and aerospace applications, and demonstrates high benefits for large scale systems due to the reduced computational effort. The proposed model can be used during the design of the battery pack for estimating the impact of degradation and thermal unbalance in a pack. Look-up-tables can be carried out to describe the behavior of battery pack at steady-state conditions and can be used by the Battery Management System (BMS) for on-line estimation of the operating conditions of the cells.","PeriodicalId":193529,"journal":{"name":"2019 IEEE National Aerospace and Electronics Conference (NAECON)","volume":"126 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114543075","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 14

Fast Lane Filtering for Autonomous Vehicle 自动驾驶汽车的快车道滤波

2019 IEEE National Aerospace and Electronics Conference (NAECON) Pub Date : 2019-07-01 DOI: 10.1109/NAECON46414.2019.9057872

Ying Li, Sihao Ding

引用次数: 1

Low Noise High Stability Amplifiers over Very High Frequency Range Using Mismatching Approach within Linvill Plane Simulation 林维尔平面仿真中采用错匹配方法的甚高频低噪声高稳定性放大器

2019 IEEE National Aerospace and Electronics Conference (NAECON) Pub Date : 2019-07-01 DOI: 10.1109/NAECON46414.2019.9058166

Joshua K. Woodward, M. Rizkalla

{"title":"Low Noise High Stability Amplifiers over Very High Frequency Range Using Mismatching Approach within Linvill Plane Simulation","authors":"Joshua K. Woodward, M. Rizkalla","doi":"10.1109/NAECON46414.2019.9058166","DOIUrl":"https://doi.org/10.1109/NAECON46414.2019.9058166","url":null,"abstract":"A software approach was utilized to study the gain stability over a long frequency range in the order of 10 decades. The approach addresses the input and output power representations on the Linvill plane over a given frequency range. The study considers the mismatching approach by adding input and output admittances to keep the transducer gain of the system stable with a high stern stability factor. The study was extended to cover optimum noise figure over a frequency range of 10Hz-100GHz. The new selection technique uses a MATLAB script to calculate the Y parameters of a common emitter BJT amplifier for a wide frequency band. From the Y parameters, calculations for the optimum shunt admittances for the source and load are made based on a customizable threshold for the Stern stability factor. Additional calculations are made to optimize the source conductance to achieve the lowest noise figure. The program then calculates the noise figure at optimum stability and the stability factor at optimum noise. Initially, the device was instable for 2 decades within the MHz range, and after applying the described approach, the device was stable for the entire 10Hz100GHz frequency range. The transducer gain of the stabilized device was lower than that of the initial instable device.","PeriodicalId":193529,"journal":{"name":"2019 IEEE National Aerospace and Electronics Conference (NAECON)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129808317","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

The use of a Reflectometer as a Monostatic Radar for Measuring Aircraft Structural Flutter 用反射计作为单站雷达测量飞机结构颤振

2019 IEEE National Aerospace and Electronics Conference (NAECON) Pub Date : 2019-07-01 DOI: 10.1109/NAECON46414.2019.9058150

W. Wilson, J. P. Moore, Katelyn R. Brinker

引用次数: 2

Cluster-Based Hungarian Approach to Task Allocation for Unmanned Aerial Vehicles 基于聚类的无人机任务分配匈牙利方法

2019 IEEE National Aerospace and Electronics Conference (NAECON) Pub Date : 2019-07-01 DOI: 10.1109/NAECON46414.2019.9057847

A. Samiei, Sarah Ismail, Liang Sun

引用次数: 7

Deep Learning Ensemble Methods for Skin Lesion Analysis towards Melanoma Detection 面向黑色素瘤检测的皮肤损伤分析的深度学习集成方法

2019 IEEE National Aerospace and Electronics Conference (NAECON) Pub Date : 2019-07-01 DOI: 10.1109/NAECON46414.2019.9058245

Redha Ali, R. Hardie, Barath Narayanan Narayanan, Supun de Silva

{"title":"Deep Learning Ensemble Methods for Skin Lesion Analysis towards Melanoma Detection","authors":"Redha Ali, R. Hardie, Barath Narayanan Narayanan, Supun de Silva","doi":"10.1109/NAECON46414.2019.9058245","DOIUrl":"https://doi.org/10.1109/NAECON46414.2019.9058245","url":null,"abstract":"Skin cancer has a significant impact across the world. Melanoma is a malignant form of skin cancer. Skin lesion segmentation is an important step in computer-aided diagnosis (CAD) for automated diagnosis of melanoma. In this paper, we describe our research work and the submission to the International Skin Imaging Collaborations (ISIC) 2018 Challenge in Skin Lesion Analysis Towards Melanoma Detection. We propose Convolutional Neural Network (CNN) based ensemble methods for improving the existing performance of lesion segmentation. The proposed ensemble technique includes VGG19-UNet, DeeplabV3+ and other preprocessing methodologies. Extensive experiments are conducted on the ISIC 2018 challenge dataset to demonstrate the efficacy of the proposed model. For evaluation, we utilize the ISIC 2018 datasets that contains 2,594 dermoscopy images with their ground truth segmentation masks. We randomly divided the dataset into 80% for training and 20% for validation. Our proposed model provided an overall accuracy of 93.6%, average Jaccard Index of 0.815, and dice coefficient of 0.887 on the testing dataset.","PeriodicalId":193529,"journal":{"name":"2019 IEEE National Aerospace and Electronics Conference (NAECON)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116508784","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 27